Feature Extraction and Classification of Four-Class Motor Imagery Signals Based on LCD and CSP
Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering · 2017
The common spatial pattern (CSP) can effectively extract the spatial information of motor imagery (MI) signals, but ignores time and frequency domain information of EEG signals.In order to overcome this problem, a new method is proposed in this paper, which combines the CSP method with the time-frequency analysis method Local Characteristic-scale Decomposition (LCD) to extract the timefrequency information and improve the classification accuracy.The effectiveness of the algorithm was verified by conducting experiments with the BCI competition dataset.The results show that the proposed method improves the recognition rate of MI signals, and has potential for the application of portable BCI systems in rehabilitation field.